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LAP#1 - Problem Solving,
by Michael Beard 1994



STATEMENT OF PRINCIPLE/THEORY

In the incredibly complex world of drag racing, there are innumerable problems to overcome. Although these problems all lead to the single goal of winning, the types of obstacles are as diverse as their solutions. When actually solving any one of these tasks, no one really thinks about how they are going about it, but with some afterthought, it becomes clear that solving methods follow a combination of John Dewey's pragmatic approach to problem solving and Wolfgang Koehler's Gestalt view of problem solving.



SUMMARY OF PRINCIPLE/THEORY

The two principles have some common ground, some opposing pieces, but most importantly, they should not be exclusive. A combination of the underlying logic to both Dewey's and Koehler's theories yields an excellent model for real world problem solving. Compiled, the new model, (let us call it the Beard Task Principles) would be constructed in the following fashion. First, it is obvious that in order to solve a problem, we must know what that problem is. In the case of drag racers, we often find that problems are not readily apparent. When I lose a race, I know there must be a problem. I must then analyze every bit of information I can gather from the race to determine what the issue was. Then, following Dewey's model, I develop several approaches with which to tackle the dilemma. If I red-lighted, a false start, then there are many possible causes for it. I mentally scan the reasons for losing the race, and discard the least likely ones. With more than one likely cause, I use any following races to isolate the problem, and hopefully cure it, thus testing my theoretical solutions. After several unsuccessful attempts, Koehler's Gestalt principle correctly predicts the insight that allows me to instantly realize the cause of my lost races, and what to do about them!



ANALYSIS OF PERSONAL LEARNING EXPERIENCES

During every season of NHRA drag racing, I felt that I was driving the best that I could. When I looked back upon a past year, however, I quickly realized that there was always tremendous room for improvement. Even after three and a half years of racing, I was still not at the highest level of attainable performance I could expect from myself. One factor that improved my driving was my fairly new ability to analyze my skills shortly after or even during a race, instead of months or even years later. Discovering what makes a racer lose would not help him if it was too late to apply that new knowledge! In this past season, I was enjoying a fair degree of success, but I wanted more from myself. Thus it occurred to me that I had a problem. In order to find out how to win more races, I took a look at my present performances, as well as how I had done in the past.

As I pondered my logbook of records from previous years, I discovered that my reaction times were not as good as I had thought, although they were better this year. I compiled all the statistics on how many races I won or lost in which reaction times were a major factor, and decided that it was a significant amount of races. I then looked at my current reaction times since this seemed to be the problematic category, and noticed a trend of times between .540 and .560 seconds. (For reference, .500, or half a second is a perfect reaction time.) Another look at my records showed that the vast majority of races were won or lost by two or three hundredths of a second. It reasoned then that if I could consistently get reaction times that were in the .510 to .530 range, I would win many more races! With renewed determination, I hit the track the following weekend with a goal in sight. With great concentration, I achieved reaction times of none other than ... .540's. The simple solution to winning races had failed to have any effect on my performance.

Armed with one failed hypothesis, I decided to turn to drastic measures. With a racing equipment catalog in one hand, and the almighty pen in the other, I ordered a practice tree. This fancy little device simulates the starting lights at the drag strip with the most precision possible. With an enormous amount of options with which to hone my driving skills, I practiced all week. The little amber bulbs flashed on the electronic box for hours until I finally achieved the ability to hit consistently quick reaction times. Once again, with unflagging determination, I returned to the track. At the end of the day, my records showed the fruits of my labors ... .540 reaction times. Frustrated with another failed hypothesis that had seemed flawless, I turned back the dilemma at hand. Simple reasoning prevailed: "If I practice and get .520's, but get .540's at the track, I must be practicing wrong!" With that sudden intuition, everything was perfectly clear to me. I changed the options on the practice tree to slow my car reaction times by the difference of two hundredths of a second, and practiced all week long again. Finally, with grim determination, I ventured back to the drag strip, and I was not surprised with the results. My reaction times were .520's all day long, and I won the entire event! Since that time, in the last five races of the season, my average reaction time was a .518, and I finished the year in sixth place.



APPLICATION TO FUTURE TEACHING

As both the teacher and the learner in a drag racing setting, I now know that I can use the Beard Task Principles to achieve my goals more readily. Since I have already solved one problem related to winning races, I can easily adjust my learning technique to avoid unlikely solutions, and thus resolve conflicts more quickly. Until I win every race in which I compete, there is something that I am doing wrong that I can fix. Although I have been in twenty-seven final rounds in three and a half years, the track holds at least thirty races a year, which leaves plenty of room for improvement. I believe that I have conquered the problems that can occur on the starting line, but I know that how I drive near the finish line has still lost many races for me.

In bracket racing, cars are handicapped, giving the slower cars a head start. Since the times used to handicap the cars are chosen by the driver, choosing a slower time would give a longer head start for the slower car, and thus an easy win. To avoid this conflict, NHRA uses a system such that if a car runs a quicker time than the driver predicted, he loses. The key to winning races is then to have a very consistent car, and to run exactly what you predicted. This becomes very complicated, since the two cars will be very close at the finish line, but each driver wants to get there by the least amount of time possible to avoid going faster than his prediction. Matters are further complicated by all the variables determining where the cars meet at the finish. In some cases, I want to tap the brakes to reach the finish first by the least amount of time, or sometimes I may even hit the brakes hard right at the finish in the hopes that my opponent will hit the finish first, but run too fast! It is these instances in which it becomes extremely hard to make such a split second decision, and make it be the right one. Driving at the finish line is arguably the most challenging of disciplines for bracket racers.

Despite the difficulty of "top-end" racing, I know how to improve my technique with the Beard Task Principles. I will use my proven method of problem definition and hypothesis creation by examining my logbook to see what causes me to lose. Once I have a firm list of "bad decisions," I will be able to envision the races in my mind, playing out various scenarios until I find the methods that will work. Since every race is wholly different from the last, I will group these hypothetical "win" situations into a small number of categories in which most races fall. With a quickly retrievable database of possible races, I should be able to make the right decisions more readily, and thus win more races. Since the current racing season lies under several feet of snow, testing of this hypothesis has been postponed.



EVALUATION

With the successful implementation of the Beard Task Principles shown here, it is easy to see that future problems I tackle in the same way I will eventually solve suitably. The one burden that remains to trouble the proposed principles is time. As stated before, time is the enemy involved in drag racing related problems. If insight does not present itself quickly, a driver wastes much time and money trying to discover why he is not winning races.


Copyright 1996-1999 Michael G. Beard

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